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New techniques for the remote sensing of foliar nitrogen concentration in forest ecosystems.

During my Doctoral study I researched about the remote detection of canopy N concentration in forest stands, its potentials and problems, under many overlapping perspectives. The study consisted of three parts.
In S. Rossore 2000 dataset analysis, I tested regressions between N concentration and NIR reflectances derived from different sources (field samples, airborne and satellite sensors). The analysis was further expanded using a larger dataset acquired in year 2009 as part of a new campaign funded by the ESA.
In both cases, a good correlation was observed between Landsat NIR, using both TM (2009) and ETM+ (2000) imagery, and N concentration measured by a CHN elemental analyzer.
Concerning airborne sensors I did not obtain the same good results, mainly because of the large FOV of the two instruments, and to the anisotropy of vegetation reflectance. We also tested the relation between ground based ASD measures and nitrogen concentration, obtaining really good results. Thus, I decided to expand my study to the regional level, focusing only on field and satellite measures.
I analyzed a large dataset for the whole of Catalonia, Spain; MODIS imagery was used, in consideration of its spectral characteristics and despite its rather poor spatial resolution. Also in this case a regression between nitrogen concentration and reflectances was found, but not so good as in previous experiences. Moreover, vegetation type was found to play an important role in the observed relationship.
We concluded that MODIS is not the most suitable satellite sensor in realities like Italy and Catalonia, which present a patchy and inhomogeneous vegetation cover; so it could be utilized for the parameterization of eco-physiological and biogeochemical models, but not for really local nitrogen estimate. Thus multispectral sensors similar to Landsat Thematic Mapper, with better spatial resolution, could be the most appropriate sensors to estimate N concentration.

Identiferoai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:5674
Date09 April 2013
CreatorsMezzini, Elena <1984>
ContributorsMagnani, Federico
PublisherAlma Mater Studiorum - Università di Bologna
Source SetsUniversità di Bologna
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral Thesis, PeerReviewed
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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